The Impact of COVID-19 Management Policies Tailored to Airborne SARS-CoV-2 Transmission: Policy Analysis

BackgroundDaily new COVID-19 cases from January to April 2020 demonstrate varying patterns of SARS-CoV-2 transmission across different geographical regions. Constant infection rates were observed in some countries, whereas China and South Korea had a very low number of daily new cases. In fact, China and South Korea successfully and quickly flattened their COVID-19 curve. To understand why this was the case, this paper investigated possible aerosol-forming patterns in the atmosphere and their relationship to the policy measures adopted by select countries.ObjectiveThe main research objective was to compare the outcomes of policies adopted by countries between January and April 2020. Policies included physical distancing measures that in some cases were associated with mask use and city disinfection. We investigated whether the type of social distancing framework adopted by some countries (ie, without mask use and city disinfection) led to the continual dissemination of SARS-CoV-2 (daily new cases) in the community during the study period.MethodsWe examined the policies used as a preventive framework for virus community transmission in some countries and compared them to the policies adopted by China and South Korea. Countries that used a policy of social distancing by 1-2 m were divided into two groups. The first group consisted of countries that implemented social distancing (1-2 m) only, and the second comprised China and South Korea, which implemented distancing with additional transmission/isolation measures using masks and city disinfection. Global daily case maps from Johns Hopkins University were used to provide time-series data for the analysis.ResultsThe results showed that virus transmission was reduced due to policies affecting SARS-CoV-2 propagation over time. Remarkably, China and South Korea obtained substantially better results than other countries at the beginning of the epidemic due to their adoption of social distancing (1-2 m) with the additional use of masks and sanitization (city disinfection). These measures proved to be effective due to the atmosphere carrier potential of SARS-CoV-2 transmission.ConclusionsOur findings confirm that social distancing by 1-2 m with mask use and city disinfection yields positive outcomes. These strategies should be incorporated into prevention and control policies and be adopted both globally and by individuals as a method to fight the COVID-19 pandemic.     

新型冠状病毒肺炎两种不同流行模式及其防控效果比较：基于广州和温州市的分析

目的 比较广州、温州市两个城市新型冠状病毒肺炎（COVID-19）的流行模式,并评估两个城市疫情的防控效果。方法 获取截至2020年2月29日广州和温州市COVID-19确诊病例的个案数据,绘制两个城市疫情的流行曲线,收集不同时间的防控措施,计算在两个城市的实时再生数。结果 广州和温州市分别纳入确诊病例346例和465例,两个城市病例均集中在30～59岁（广州市：54.9%;温州市：70.3%）。流行曲线显示广州和温州市的每日发病数分别在1月27日与1月26日到达峰值,随后出现下降趋势。两个城市的发病高峰均出现在湖北省输入病例的抵达高峰后,且温州市的湖北省输入病例的抵达高峰早于广州市。广州市一直以输入病例为主,温州市从前期的以输入病例为主转变为后期以本地病例为主。虽然两个城市流行模式存在差异,在采取了有力的防控措施后,两个城市均取得了较好的防控效果。结论 COVID-19输入疫情可导致两种不同的流行模式,但采取强有力的防控措施,均能有效控制疫情蔓延。     

中国新型冠状病毒肺炎疫情基本再生数评估

目的 目前湖北省的新型冠状病毒肺炎(COVID-19)确诊和疑似病例的数量仍在增加。国内外多个团队对疫情发展进行了模型预测,但结论并不统一。因此,开展本次疫情的预测模型研究、评估COVID-19的基本再生数(basic reproduction number,R₀),对于评估病毒的传播能力以及一系列控制措施的效果具有重要意义。方法 收集从湖北省2020年1月17日到2月8日期间每天报告的确诊病例数等数据,分别采用指数增长方法(exponential growth,EG)、极大似然法(maximum likelihood estimation,ML)、序贯贝叶斯方法(sequential Bayesian method,SB)和时间相关基本再生数(time dependent reproduction numbers,TD)估计R₀值。结果 由观测病例数和4种方法预测的病例数的拟合情况可知,EG方法拟合效果最优。EG方法估计COVID-19湖北省R₀的值为3.49(95%CI:3.42~3.58)。采取封城控制手段期间,EG方法估算R₀值为2.95(95%CI:2.86~3.03)。结论 在传染病流行初期,适合采用EG方法估算R₀。同时需要采取及时有效的控制措施,进一步降低COVID-19的传播速率。     

构建境外输入新型冠状病毒肺炎病例的快速风险评估体系

目的:构建境外输入新型冠状病毒肺炎（新冠肺炎）病例的快速风险评估体系,为口岸疫情防控提供参考依据。方法:收集2021年7-8月12个关注国家的新冠肺炎疫情流行和防控情况,从12个方面构建境外输入病例的快速风险评估体系,利用风险矩阵法开展快速风险评估。结果:评估结果显示,12个关注国家均为境外输入病例的高风险地区或极高风...     

基于动态基本再生数的新型冠状病毒肺炎疫情防控现状评估

目的 对全国各省份的新型冠状病毒肺炎(COVID-19)疫情防控现状进行分析,建立预测模型预估现有防控措施预期成效,为决策部门提供科学信息。方法 基于COVID-19疫情网络公开数据,估计全国、各省份以及武汉市不同时间基本再生数(R0)的动态变化R₀(t),以评估在现有防控措施下,COVID-19传染速率随时间变化的趋势,预估现有防控措施的预期成效。结果 从结果稳定性考虑,选择累积确诊病例数>100例的地区进行分析,共24个省份纳入分析。在疫情初期,全国整体R₀(t)不稳定,数值较大,误差也较大。随着防控措施的进一步加强,R₀(t)普遍在1月下旬开始呈现下降趋势,2月始下降趋势稳定。截至数据分析日,纳入分析的24个省份中已有18个省份(75%)R₀(t)降到1以下。这为有条件地开放人员流动提供了信息。结论 动态R₀(t)有助于动态评估COVID-19传染速率变化情况,本次疫情防控措施已初显成效,如能继续保持,全国疫情有望短期内得到全面控制。     

上海市新型冠状病毒肺炎早期境外输入病例流行特征及防控措施分析

目的 分析上海市新型冠状病毒肺炎（COVID-19）早期境外输入病例流行特征及防控措施,为输入性疫情的防控工作提供参考依据。方法 资料来源于全国传染病报告信息管理系统截至2020年3月30日上海市COVID-19境外输入病例数据及上海市各级CDC流行病学调查报告,相关防控措施信息来源于政府相关部门官网及发布平台。采用EpiData 3.1、Excel 2019和SAS 9.4软件进行数据整理与统计学分析。结果 截至2020年3月30日,上海市累计报告境外输入病例171例（确诊病例170例,无症状感染者1例）。其中,中国籍122例（71.3%,122/171）,外籍49例（28.7%,49/171）;年龄中位数为23（P₂₅,P₇₅：18,35）岁,男女性别比为1.3∶1,学生占56.6%（97/171）;入境前发病者占45.6%（78/171）;临床分型为轻/普通型病例占96.5%（165/171）,中国籍和外籍病例的临床分型差异无统计学意义。流行曲线按确诊日期于3月24日达到峰值,随着防控措施“口岸联防联控机制闭环管理模式”落实,病例数逐渐下降。171例病例来源国主要为英国（37.3%,64例）、美国（18.6%,32例）、法国（11.0%,19例）和意大利（9.4%,16例）等24个国家及地区。需中转至国内21个省（自治区、直辖市）的病例占40.4%（69/171）。病例发现方式主要为海关检疫和社区留验点,分别占43.9%（75/171）和31.0%（53/171）。结论 上海市COVID-19早期境外输入病例以年轻人和学生为主,各国输入风险与其疫情严重程度基本一致。“口岸联防联控机制闭环管理模式”对境外输入病例的发现及管理效果明显。     

Associations Between Conventional Healthy Behaviors and Social Distancing During the COVID-19 Pandemic: Evidence From the 2020 Community Health Survey in Korea

Objectives:Many studies have shown that social distancing, as a non-pharmaceutical intervention (NPI) that is one of the various measures against coronavirus disease 2019 (COVID-19), is an effective preventive measure to suppress the spread of infectious diseases. This study explored the relationships between traditional health-related behaviors in Korea and social distancing practices during the COVID-19 pandemic.Methods:Data were obtained from the 2020 Community Health Survey conducted by the Korea Disease Control and Prevention Agency (n=98 149). The dependent variable was the degree of social distancing practice to cope with the COVID-19 epidemic. Independent variables included health-risk behaviors and health-promoting behaviors. The moderators were vaccination and unmet medical needs. Predictors affecting the practice of social distancing were identified through hierarchical multiple logistic regression analysis.Results:Smokers (adjusted odds ratio [aOR], 0.924) and frequent drinkers (aOR, 0.933) were more likely not to practice social distancing. A greater degree of physical activity was associated with a higher likelihood of practicing social distancing (aOR, 1.029). People who were vaccinated against influenza were more likely to practice social distancing than those who were not (aOR, 1.150). However, people with unmet medical needs were less likely to practice social distancing than those who did not experience unmet medical needs (aOR, 0.757).Conclusions:Social distancing practices were related to traditional health behaviors such as smoking, drinking, and physical activity. Their patterns showed a clustering effect of health inequality. Therefore, when establishing a strategy to strengthen social distancing, a strategy to protect the vulnerable should be considered concomitantly.     

天津市境外输入性新型冠状病毒感染者流行病学特征分析

目的 描述天津市境外输入性新型冠状病毒感染者流行病学特征,为境外输入疫情防控、人员风险评估提供参考。方法 输入性感染者信息来源于中国疾病预防控制信息系统传染病报告信息管理系统,收集2020年3月15日至2021年8月31日由天津市航空口岸入境的疫情输入信息,及各级疾病预防控制中心流行病学报告,采用Excel 2010、SPSS 25.0和R软件进行整理与统计学分析。结果 2020年3月15日至2021年8月31日,天津市累计报告境外输入性新型冠状病毒感染者606例,纳入分析552例,男女性别比例1.8：1,年龄3~77岁,以20~39岁为主（59.8%）。14 d内国际旅居史涉及欧洲地区（43.8%,242例）、非洲地区（25.2%,139例）、美洲地区（15.4%,85例）、亚洲地区（15.6%,86例）。秋、冬季确诊病例占比较高。观察期内,海关入境检疫排查发现感染者比例逐渐下降,个人健康申报、医学隔离监测比例升高。输入性感染者自入境至确诊的时间间隔有延长趋势。结论 天津市航空口岸入境的输入性新型冠状病毒感染者入境首日被发现的比例下降,排查发现感染者的时间间隔有延长趋势,值得警惕和关注。     

The Influence of Social Distancing on COVID-19 Mortality in US Counties: Cross-sectional Study

BackgroundPrevious studies on the impact of social distancing on COVID-19 mortality in the United States have predominantly examined this relationship at the national level and have not separated COVID-19 deaths in nursing homes from total COVID-19 deaths. This approach may obscure differences in social distancing behaviors by county in addition to the actual effectiveness of social distancing in preventing COVID-19 deaths.ObjectiveThis study aimed to determine the influence of county-level social distancing behavior on COVID-19 mortality (deaths per 100,000 people) across US counties over the period of the implementation of stay-at-home orders in most US states (March-May 2020).MethodsUsing social distancing data from tracked mobile phones in all US counties, we estimated the relationship between social distancing (average proportion of mobile phone usage outside of home between March and May 2020) and COVID-19 mortality (when the state in which the county is located reported its first confirmed case of COVID-19 and up to May 31, 2020) with a mixed-effects negative binomial model while distinguishing COVID-19 deaths in nursing homes from total COVID-19 deaths and accounting for social distancing– and COVID-19–related factors (including the period between the report of the first confirmed case of COVID-19 and May 31, 2020; population density; social vulnerability; and hospital resource availability). Results from the mixed-effects negative binomial model were then used to generate marginal effects at the mean, which helped separate the influence of social distancing on COVID-19 deaths from other covariates while calculating COVID-19 deaths per 100,000 people.ResultsWe observed that a 1% increase in average mobile phone usage outside of home between March and May 2020 led to a significant increase in COVID-19 mortality by a factor of 1.18 (P<.001), while every 1% increase in the average proportion of mobile phone usage outside of home in February 2020 was found to significantly decrease COVID-19 mortality by a factor of 0.90 (P<.001).ConclusionsAs stay-at-home orders have been lifted in many US states, continued adherence to other social distancing measures, such as avoiding large gatherings and maintaining physical distance in public, are key to preventing additional COVID-19 deaths in counties across the country.     

宁波市15起新型冠状病毒肺炎聚集性疫情的传播力研究

目的 描述新型冠状病毒肺炎（COVID-19）聚集性疫情病例的基本特征。方法 收集15起COVID-19聚集性疫情病例的基本信息,采用伽马分布拟合病例代际间隔时间（Tg）,使用基于SEIR模型计算基本再生数（R₀）。结果 15起聚集性疫情中共有确诊病例52例、涉及5例核酸阳性无症状感染者。病例发病时间主要集中在1月23日至2月4日,以女性为主,潜伏期为（6.11±3.38）d。Tg为（6.93±3.70）d,在<60岁、≥60岁组及男、女性之间,Tg差异无统计学意义（P=0.551）。按照本研究估算的Tg计算,宁波市新冠肺炎感染的R₀为3.06（95% CI：2.64~3.51）;按照文献报告的病例Tg为7.5 d计算,R₀为3.32（95% CI：2.51~9.38）。结论 COVID-19聚集性疫情病例的Tg在不同年龄、性别间差异不大,COVID-19早期致病和传播力较高。     

Quantifying the Effect of Public Activity Intervention Policies on COVID-19 Pandemic Containment Using Epidemiologic Data From 145 Countries

ObjectivesMost countries have adopted public activity intervention policies to control the coronavirus disease 2019 (COVID-19) pandemic. Nevertheless, empirical evidence of the effectiveness of different interventions on the containment of the epidemic was inconsistent.MethodsWe retrieved time-series intervention policy data for 145 countries from the Oxford COVID-19 Government Response Tracker from December 31, 2019, to July 1, 2020, which included 8 containment and closure policies. We investigated the association of timeliness, stringency, and duration of intervention with cumulative infections per million population on July 1, 2020. We introduced a novel counterfactual estimator to estimate the effects of these interventions on COVID-19 time-varying reproduction number (R_t).ResultsThere is some evidence that earlier implementation, longer durations, and more strictness of intervention policies at the early but not middle stage were associated with reduced infections of COVID-19. The counterfactual model proved to have controlled for unobserved time-varying confounders and established a valid causal relationship between policy intervention and R_t reduction. The average intervention effect revealed that all interventions significantly decrease R_t after their implementation. R_t decreased by 30% (22%-41%) in 25 to 32 days after policy intervention. Among the 8 interventions, school closing, workplace closing, and public events cancellation demonstrated the strongest and most consistent evidence of associations.ConclusionsOur study provides more reliable evidence of the quantitative effects of policy interventions on the COVID-19 epidemic and suggested that stricter public activity interventions should be implemented at the early stage of the epidemic for improved containment.     

广州市2起由新型冠状病毒奥密克戎变异株引起的本地疫情流行病学参数研究

目的 本研究旨在估计广州市2起由新型冠状病毒（新冠病毒）奥密克戎变异株（BA.2）引起的本地疫情的潜伏期、序列间隔和基本再生数（R₀）等流行病学参数,探索不同场所聚集性对R₀的影响,为奥密克戎变异株疫情防控提供科学依据。方法 收集2022年4-5月广州市2起新冠病毒奥密克戎变异株本地疫情病例数据,使用Weibull、Gamma和lognormal分布对奥密克戎变异株本地疫情的潜伏期、序列间隔分布进行估计,采用指数增长法和极大似然法估计R₀。结果 两起疫情中位潜伏期为2.94（95%CI：2.52~3.38）d;中位序列间隔为3.32（95%CI：2.89~3.81）d。小型场所聚集性疫情R₀为4.40（95%CI：3.95~4.85）,机场聚集性疫情R₀为11.35（95%CI：11.02~11.67）。结论 广州市2起由新冠病毒奥密克戎变异株引起的本地疫情潜伏期较德尔塔变异株明显缩短。场所聚集程度越高,R₀越大,传播速度越快,易呈现暴发疫情,应及时调整防控策略。     

Health disparity in the spread of COVID-19: Evidence from social distancing,risk of interactions,and access to testing

Objective– To identify and assess whether three major risk factors that due to differential access to flexible resources might help explain disparities in the spread of COVID-19 across communities with different socioeconomic status, including socioeconomic inequalities in social distancing, the potential risk of interpersonal interactions, and access to testing.MethodsAnalysis uses ZIP code level weekly COVID-19 new cases, weekly population movement flows, weekly close-contact index, and weekly COVID-19 testing sites in Southern California from March 2020 to April 2021, merged with the U.S. census data to measure ZIP code level socioeconomic status and cofounders. This study first develops the measures for social distancing, the potential risk of interactions, and access to testing. Then we employ a spatial lag regression model to quantify the contributions of those factors to weekly COVID-19 case growth.ResultsResults identify that, during the first COVID-19 wave, new case growth of the low-income group is two times higher than that of the high-income group. The COVID-19 case disparity widens to four times in the second COVID-19 wave. We also observed significant disparities in social distancing, the potential risk of interactions, and access to testing among communities with different socioeconomic status. In addition, all of them contribute to the disparities of COVID-19 incidences. Among them, the potential risk of interactions is the most important contributor, whereas testing accessibility contributes least. We also found that close-contact is a more effective measure of social distancing than population movements in examining the spread of COVID-19.Conclusion– This study answers critically unaddressed questions about health disparities in the spread of COVID-19 by assessing factors that might explain why the spread is different in different groups.     

The Effectiveness of Community-based Social Distancing for Mitigating the Spread of the COVID-19 Pandemic in Turkey

ObjectivesThe objective of this study was to demonstrate the effects of community-based social distancing interventions after the first coronavirus disease 2019 (COVID-19) case in Turkey on the course of the pandemic and to determine the number of prevented cases.MethodsIn this ecological study, the interventions implemented in response to the first COVID-19 cases in Turkey were evaluated and the effect of the interventions was demonstrated by calculating the effective reproduction number (R_t) of severe acute respiratory syndrome coro navirus 2 (SARS-CoV-2) when people complied with community-based social distancing rules.ResultsGoogle mobility scores decreased by an average of 36.33±22.41 points (range, 2.60 to 84.80) and a median of 43.80 points (interquartile range [IQR], 24.90 to 50.25). The interventions caused the calculated R_t to decrease to 1.88 (95% confidence interval, 1.87 to 1.89). The median growth rate was 19.90% (IQR, 10.90 to 53.90). A positive correlation was found between Google mobility data and R_t (r=0.783; p<0.001). The expected number of cases if the growth rate had not changed was predicted according to Google mobility categories, and it was estimated to be 1 381 922 in total. Thus, community-based interventions were estimated to have prevented 1 299 593 people from being infected.ConclusionsCommunity-based social distancing interventions significantly decreased the R_t of COVID-19 by reducing human mobility, and thereby prevented many people from becoming infected. Another important result of this study is that it shows health policy-makers that data on human mobility in the community obtained via mobile phones can be a guide for measures to be taken.     

广西境外输入性COVID-19感染者流行病学及病毒基因特征

目的  分析广西壮族自治区(广西)境外输入性COVID-19感染者的流行病学特点及病毒基因特征,为境外输入疫情防控提供依据。方法  收集2020年3月1日―2022年3月31日广西境外输入性COVID-19感染者的相关信息,使用CLC Genomics Workbench软件进行序列拼接,MEGA软件构建系统进化树。结果  广西累计报告输入性感染者1 662例,纳入分析1 643例,平均年龄为37.4岁,男女比例为6.4∶1,68.4%接种过疫苗。输入性感染者来源国以越南为主(92.5%),入境口岸以凭祥友谊关为主(87.4%)。2020年输入性感染者主要为B.1.351和B.1.1分支,2021年主要为Delta分支,2022年主要为Omicron分支。结论  广西持续存在从东南亚疫情高风险国家通过口岸输入疫情的风险,输入感染者的病毒主要为当年的关切变异株(variants of concern,VOC),口岸疫情防控形势严峻,需要持续关注输入性病例。     

陕西省新型冠状病毒肺炎流行病学特征分析

目的 了解陕西省新型冠状病毒肺炎（COVID-19）的发病趋势及流行特征。方法 收集陕西省截至2020年2月22日COVID-19的疫情数据,进行流行病学描述性分析。结果 陕西省共报告245例COVID-19确诊病例,全省累积报告的确诊病例以轻型、普通型为主（87.76%）,随着时间的推移,出现确诊病例的地区不断扩大,以西安市报告病例数最多（占全省报告总病例数近一半）。陕西省由输入型病例逐渐转为本地病例为主,而本地病例的传播途径主要以家庭聚集性传播为主。陕西省不同来源确诊病例均造成了二代病例传播。2月7日之后报告病例数开始波动下降并逐渐趋于平稳,目前陕西省疫情发展处于归零期。结论 陕西省的总体疫情形势已趋向缓和,但考虑到复工返学的到来,同时随着境外输入病例的不断增加,防控工作将面临新的挑战。     

新型冠状病毒肺炎的早期传染病流行病学参数估计研究

目的 研究截至2020年1月31日新型冠状病毒肺炎疫情的早期流行动态,估计该疫情的基本再生数(R0)、潜伏期和世代间隔等流行病学参数。方法 使用威布尔、伽马和对数正态分布拟合从报告病例信息中获取的潜伏期和世代间隔数据的概率分布,采用Akaike信息准则确定最优模型。考虑到疫情还在流行中,应用指数增长模型拟合了2020年1月15-31日的疫情数据,并利用指数增长法、最大似然法和SEIR模型估计R0。结果 截至2020年1月26日早期疫情遵循指数增长模式,随后增长趋势有所减缓。平均潜伏期为5.01(95%CI:4.31~5.69)d;平均世代间隔为6.03(95%CI:5.20~6.91)d。3种方法估计的R0分别为3.74(95%CI:3.63~3.87),3.16(95%CI:2.90~3.43)和3.91(95%CI:3.71~4.11)。结论 世代间隔和潜伏期都更符合伽马分布,世代间隔均值比潜伏期均值长1.02 d;R0较高,疫情形势较为严峻;1月26日是疫情动态的一个转折点,之后疫情增长趋势有所减缓。     

Changes in the incidence of seasonal influenza in response to COVID-19 social distancing measures: an observational study based on Canada’s national influenza surveillance system

ObjectivesSeasonal influenza is an acute respiratory infection that presents a significant annual burden to Canadians and the Canadian healthcare system. Social distancing measures that were implemented to control the 2019–2020 novel coronavirus outbreak were investigated for their ability to lessen the incident cases of seasonal influenza.MethodsWe conducted an ecological study using data from Canada’s national influenza surveillance system to investigate whether social distancing measures to control COVID-19 reduced the incident cases of seasonal influenza. Data taken from three separate time frames facilitated analysis of the 2019–2020 influenza season prior to, during, and following the implementation of COVID-19-related measures and enabled comparisons with the same time periods during three preceding flu seasons. The incidence, which referred to the number of laboratory-confirmed cases of specific influenza strains, was of primary focus. Further analysis determined the number of new laboratory-confirmed influenza or influenza-like illness outbreaks.ResultsOur results indicate a premature end to the 2019–2020 influenza season, with significantly fewer cases and outbreaks being recorded following the enactment of many COVID-19 social distancing policies. The incidence of influenza strains A (H3N2), A (unsubtyped), and B were all significantly lower at the tail end of the 2019–2020 influenza season as compared with preceding seasons (p = 0.0003, p = 0.0007, p = 0.0019).ConclusionSpecific social distancing measures and behaviours may serve as effective tools to limit the spread of influenza transmission moving forward, as they become more familiar.Supplementary InformationThe online version contains supplementary material available at 10.17269/s41997-021-00509-4.     

Loneliness in Europe before and during the COVID-19 pandemic

ObjectiveThe purpose of the study is to examine the prevalence of loneliness in Europe in 2016 and during the first months – April-July 2020 – of the COVID-19 pandemic, and to assess whether the risk factors associated with loneliness have changed after the outbreak of the pandemic.MethodThe analysis is based on two cross-country surveys, namely the 2016 European Quality of Life Survey and the 2020 Living, Working and COVID-19 Online Survey.ResultsThe COVID-19 pandemic has magnified already worrying levels of loneliness in Europe. Young adults have been the most severely hit by social distancing measures. Living alone has made social distancing measures more painful. Health and financial status are strong associates of loneliness, irrespective of the time period.ConclusionThis analysis will help anticipate the potential consequences that forced social isolation might have triggered in the population and identify populations more vulnerable to loneliness. Further monitoring is important to assess whether the registered increase in loneliness is transient or chronic and to design targeted loneliness interventions.     

北京市新型冠状病毒Omicron变异株的传播力研究

目的 评估新型冠状病毒Omicron变异株在北京市现有防控措施下的传播力,为做好疫情防控工作提供参考依据。方法 收集北京市2022年3月7-25日报告的78例具有明确传播链的Omicron变异株感染者信息,分别采用Gamma和Weibull分布拟合潜伏期和序列间隔时间,使用马尔科夫链蒙特卡罗算法估计实时再生数（R_t）。结果 Omicron变异株感染者潜伏期M（Q₁,Q₃）为4.0（3.0,6.0）d,序列间隔时间3.0（2.0,5.0）d,序列间隔时间在未完成和已完成全程疫苗接种感染者中M（Q₁,Q₃）分别为2.0（1.0,4.0）d和4.0（2.0,6.0）d（Z=-2.12,P=0.034）,儿童和成年人感染者分别为2.0（1.5,3.0）d和4.0（2.0,6.0）d（Z=-2.02,P=0.044）,差异均有统计学意义。本轮疫情R_t初始值为4.98（95%CI： 2.22~9.04）。结论 与既往Delta变异株相比,北京市Omicron变异株的传播力较强,应持续做好常态化疫情防控和新型冠状病毒疫苗接种工作,关注儿童易感人群。